AIC is only defined up to an additive constant (as is log-likelihood). It should not surprise you that the values for AIC differ between packages.
The real question is whether the change in AIC when going form one model to anoth is the same. If not, one is wrong (at least). -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Darren M Gillis Sent: Friday, 15 October 2010 1:37 PM To: r-help@r-project.org Subject: [R] AIC in bestglm, glm, and lm - why do they differ? I recently found the "bestglm" package while trolling CRAN for a function to save some keystrokes with simple (k<10) nested models. I am interested in using the best of several nested linear models which I have explored using lm(), glm() and now bestglm(). When I compare the AIC values for the 'best' candidate model I get the same AIC values with lm() and glm() but a different AIC (and likelihood) value from bestglm(). Is this the result of some difference in likelihood calculation that I am missing in reviewing the documentation and help files? I can provide code if there is interest in looking into this, otherwise I will continue to assemble my tables the long way with glm() and lm(), though the options and potential of the bestglm() package has me very interested. Cheers, Darren Gillis Biological Sciences University of Manitoba Winnipeg, MB [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
